§3 fix: correctly distinguish DFA/SB/CB local credit vectors

Previous §3 ¶1 wrote the local loss as -<f_l, B_l^T e_T> as if it applied
to DFA, SB, and CB all three. But that's only DFA's form. SB and CB use
learned bridge networks to derive credit:

- DFA: a_l = B_l^T e_T (fixed random projection)
- State Bridge: a_l = gradient of CE(head(LN(G_psi(h_l, t_l, s))), y)
  where G_psi is a learned state predictor of h_L
- Credit Bridge: a_l = gradient of learned value net V(h_l, t_l, s)

The fix correctly writes the shared local loss form -<f_l, a_l> and
defines a_l for each method in-line. This also serves as the first
definition of SB and CB in the paper (previously they were named in
Table 1 without being defined).

Main content still ends at p9 (just slightly before the bottom margin
now); references span p9-p10 but are not counted against the 9-page
content budget. Total 17 pages.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

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